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IEEE International Conference on High Performance Computing and Communications

作者： Shan He Chunming Hu Bin Shi Tianyu Wo Bo Li State Key Laboratory of Software Development Environment (NLSDE) School of Computer Science and Engineering Beihang University Beijing China 100191

ISBN: (纸本)9781509042982

Virtual machine live migration technology allows a running VM migrates from one physical host to another with no impact on users. As the scale of distributed computing gets larger and larger, hybrid cloud, which is integrated cloud service utilizing both private and public clouds to perform distinct functions within the same organization becomes a hotspot for both academia and industry. Thus, it will be vital to migrate virtual machines in hybrid clouds. The biggest issue which VM migration in hybrid clouds faces today is how to transfer the large amount of storage data. Storage migration of virtual machine with existing mechanisms of memory migration has been studied for a long time. Unfortunately, no one can perform perfectly without modification. It is compelling to consider a new migration model and optimization methods. In this paper, we analyze the advantage and disadvantage of classical methods, and put forward a method which combines the strengths of pre-copy and post-copy migration model and we also use disk working set to optimize virtual machines storage migration. We have developed and implemented our approach to the QEMU/KVM hypervisor and run a series of experiments. The presented technique shows a reduction of up 20.5% on average of the total transfer time for most of the selected scenario. Our approach can also reduce the migration downtime in most cases.

关键词： working set virtual machine live migration storage

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SALIENCY ANALYSIS BASED ON DEPTH CONTRAST INCREASED

SALIENCY ANALYSIS BASED ON DEPTH CONTRAST INCREASED

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Hao Sheng Xiaoyu Liu Shuo Zhang State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing P.R. China

ISBN: (纸本)9781479999897

Humans can understand their surroundings by an additional depth cue that provides by stereopsis, which plays an important role in the human visual system. Recently, depth saliency has been attracted much attention. But depth image differs a lot from color image. Feature extraction in depth image is an important problem in depth saliency analysis. Previous studies always extract features from depth map directly. This paper proposes a method which can make the saliency analysis easier and more accurate by increasing the depth contrast between the salient object and distractors. Then, we extended a recent saliency analysis approach to evaluate the saliency of the difference map. Finally, after the optimization by depth information and color information the final saliency map can be obtained. Our experiments on public dataset show that our method significantly outperforms state-of-the-art.

关键词： depth information increased depth contrast saliency detection

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Mining Frequent Itemsets in Correlated Uncertain Databases

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Journal of computer science & Technology 2015年第4期30卷 696-712页

作者：童咏昕陈雷余洁莹 State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong China

Recently, with the growing popularity of Internet of Things （IoT） and pervasive computing, a large amount of uncertain data, e.g., RFID data, sensor data, real-time video data, has been collected. As one of the most fundamental issues of uncertain data mining, uncertain frequent pattern mining has attracted much attention in database and data mining communities. Although there have been some solutions for uncertain frequent pattern mining, most of them assume that the data is independent, which is not true in most real-world scenarios. Therefore, current methods that are based on the independent assumption may generate inaccurate results for correlated uncertain data. In this paper, we focus on the problem of mining frequent itemsets over correlated uncertain data, where correlation can exist in any pair of uncertain data objects （transactions）. We propose a novel probabilistic model, called Correlated Frequent Probability model （CFP model） to represent the probability distribution of support in a given correlated uncertain dataset. Based on the distribution of support derived from the CFP model, we observe that some probabilistic frequent itemsets are only frequent in several transactions with high positive correlation. In particular, the itemsets, which are global probabilistic frequent, have more significance in eliminating the influence of the existing noise and correlation in data. In order to reduce redundant frequent itemsets, we further propose a new type of patterns, called global probabilistic frequent itemsets, to identify itemsets that are always frequent in each group of transactions if the whole correlated uncertain database is divided into disjoint groups based on their correlation. To speed up the mining process, we also design a dynamic programming solution, as well as two pruning and bounding techniques. Extensive experiments on both real and synthetic datasets verify the effectiveness and e？ciency of the proposed model and algorithms.

关键词： correlation uncertain data probabilistic frequent itemset

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A new authentication protocol for healthcare applications using wireless medical sensor networks with user anonymity

A new authentication protocol for healthcare applications us...

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作者： Li, Xiong Niu, Jianwei Kumari, Saru Liao, Junguo Liang, Wei Khan, Muhammad Khurram State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing100191 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China Department of Mathematics Agra College Dr. B. R. A. University AgraUttar Pradesh282002 India Center of Excellence in Information Assurance King Saud University Riyadh Saudi Arabia

With the development and maturation of the wireless communication technologies, the wireless sensor networks have been widely applied in different environments to acquire specific information. The wireless medical sensor networks (WMSNs), as a professional application of the wireless sensor networks in medicine, have attracted more and more attention because of its potential in improving the quality of healthcare services. Through the WMSNs, the parameters of patients' vital signs can be gathered from the sensor nodes equipped on the body of the patients and then can be accessed by the healthcare professionals by using a mobile device. By reason of the open feature of wireless communication, how to guarantee secure communication becomes an important issue. On the other hand, because the vital signs parameters are sensitive to the patients' health status and no one wants to reveal it to the others except the healthcare professionals, the protection of patients' privacy becomes another key issue for WMSNs applications. User authentication protocol with anonymity is the most basic and commonly used method to resolve the security and privacy issues of WMSNs. Recently, He et al. proposed an enhanced authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, we find that their scheme is incorrect in authentication and session key agreement phase. Besides, their scheme has no wrong password detection mechanism, which will not only waste the unnecessary computation and communication costs, but also may deduce the denial of service problem. In this paper, the biometric is introduced as the third authentication factor, and a new user anonymous authentication protocol based on WMSNs is designed so as to remove the drawbacks of the protocol of He et al. Compared with previous protocols, the new presented protocol enhances the security and also keeps the computation efficiency. Copyright © 2015 John Wiley & Sons, Ltd. C

关键词： Authentication

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PERSON RE-IDENTIFICATION BASED ON HIERARCHICAL BIPARTITE GRAPH MATCHING

PERSON RE-IDENTIFICATION BASED ON HIERARCHICAL BIPARTITE GRA...

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IEEE International Conference on Image Processing

作者： Yan Huang Hao Sheng Zhang Xiong State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 P.R. China

ISBN: (纸本)9781467399623

This work proposes a novel person re-identification method based on Hierarchical Bipartite Graph Matching. Because human eyes observe person appearance roughly first and then goes further into the details gradually, our method abstracts person image from coarse to fine granularity, and finally into a three layer tree structure. Then, three bipartite graph matching methods are proposed for the matching of each layer between the trees. At the bottom layer Non-complete Bipartite Graph matching is proposed to collect matching pairs among small local regions. At the middle layer Semi-complete Bipartite Graph matching is used to deal with the problem of spatial misalignment between two person bodies. Complete Bipartite Graph matching is presented to refine the ranking result at the top layer. The effectiveness of our method is validated on the CAVIAR4REID and VIPeR datasets, and competitive results are achieved on both datasets.

关键词： Vegetation Probes Bipartite graph Visualization Cost function Training data Training

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ROBUST SALIENCY PROPAGATION BASED ON RANDOM WALKS

ROBUST SALIENCY PROPAGATION BASED ON RANDOM WALKS

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Chao Li Panwen Yang Hao Sheng State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 P.R.China

ISBN: (纸本)9781479999897

A variety saliency detection methods have been based on the background prior knowledge. Nevertheless, some image patches connected to the image boundary are foreground noise. In this paper, we propose a saliency detection algorithm which propagates coarse saliency based on robust background prior set via random walks. First, we get the robust background prior set from the initial background set which is made up by all image patches connected to the image boundary, and compute a coarse saliency map through summation of global contrast between image patch in complement set of robust background prior set and image patch in robust background set. Second, we get foreground prior set by segmenting the coarse saliency via adaptive threshold, and propagate foreground prior set via random walks. Propagated foreground prior set is integrated by Bayesian inference model and resulting a saliency map. Third, we update saliency map by hypergraph and integrate current saliency and updated saliency by weighted mean summation. Finally, results from multi-scale saliency maps are integrated by pixel-wise weighted summation. Experimental result shows that our approach outperforms state-of-art approaches on two public availab.e dataset.

关键词： saliency detection superpixels robust background random walks Bayesian inference model image patch Random walk Bayesian inference Set (Psychology) Summation Detection algorithms maps adaptive thresholding

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Weight-based sparse coding for multi-shot person re-identification

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science China(Information sciences) 2015年第10期58卷 38-52页

作者： ZHENG YanWei SHENG Hao ZHANG BeiChen ZHANG Jun XIONG Zhang State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang University Shenzhen Key Laboratory of Data Vitalization Research Institute in ShenzhenBeihang University Department of Electrical Engineering and Computer Science University of Wisconsin-Milwaukee

Person re-identification(Re-ID) is the problem of matching a person from different cameras based on appearance. It has interesting algorithm challenges and extensive practical applications. This paper presents a weight-based sparse coding approach for person re-identification. First, three hypotheses are introduced to achieve a linear combination of images based on sparse coding. Then, we convert the person re-identification problem into an optimization problem with sparse constraints. To reduce the influence of abnormal residuals caused by occlusion and body variation, a weight-based sparse coding approach is proposed to achieve the optimal weights by the ordering statistics of square residuals iteratively. Experiments on various public datasets for different multi-shot modalities have shown good performance of the proposed approach compared with other state-of-the-art ones(more than 42% and 34% at rank-1 on CAVIAR4 REID and i-LIDS, respectively).

关键词： smart city person re-identification video surveillance multi-shot weight-based sparse coding

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Performance modeling and evaluation of real-time traffic status query for intelligent traffic systems

Performance modeling and evaluation of real-time traffic sta...

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Asia-Pacific Conference on Communications

作者： Jie Ding Rui Wang Xiao Chen State Key Laboratory for Novel Software Technology Nanjing University China School of Information Engineering Yangzhou University Yangzhou China State Key Laboratory of Software Development Environment Beihang University Beijing China School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9781509006779

As product of the combination of Internet technology and sensor network, Internet of things (IoT) greatly facilitates the mutual interaction of the information world and physical world. Furthermore, with the rapid development of modern transportation systems, as a typical successful application of IoT in the real life, intelligent traffic system (ITS) has a great significance on management of the traffic information and transport infrastructure. Therefore, in order to achieve the efficient use of transportation resources, it is particularly important to evaluate and analyze the performance of ITS. In this paper, an advanced high level formalization - Performance Evaluation Process algebra (PEPA), a kind of stochastic process algebra (SPA), is adopted to model the process of real-time traffic status query in ITS. Meanwhile, by using fluid approximation approach to analyze performance of the model and then the performance parameters of the system in practical application can be achieved accurately.

关键词： Real-time systems Global Positioning System Internet of things Servers Vehicles Satellites

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Towards Better Understanding of App Functions

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Journal of computer science & Technology 2015年第5期30卷 1130-1140页

作者：童咏昕余洁莹陈雷 State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China International Research Institute for Multidisciplinary Science Beihang University Beijing 100191 China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong I(ong China

Apps are attracting more and more attention from both mobile and web platforms. Due to the self-organized nature of the current app marketplaces, the descriptions of apps are not formally written and contain a lot of noisy words and sentences. Thus, for most of the apps, the functions of them are not well documented and thus cannot be captured by app search engines easily. In this paper, we study the problem of inferring the real functions of an app by identifying the most informative words in its description. In order to utilize and integrate the diverse information of the app corpus in a proper way, we propose a probabilistic topic model to discover the latent data structure of the app corpus. The outputs of the topic model are further used to identify the function of an app and its most informative words. We verify the effectiveness of the proposed methods through extensive experiments on two real app datasets crawled from Google Play and Windows Phone Store, respectively.

关键词： app function docmnent topic model

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A modeling methodology to facilitate safety-oriented architecture design of industrial avionics software

A modeling methodology to facilitate safety-oriented archite...

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作者： Wu, Ji Yue, Tao Ali, Shaukat Zhang, Huihui State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing China Certus Software Verification and Validation Center Simula Research Laboratory Lysaker Norway

Summary Ensuring that avionics software meets safety requirements at each development stage is very important to warrant the safe operation of an avionics system. Many safety requirements are imposed by various standards and industrial regulations that must be met by avionics software. One of such standards is DO-178B/C, which provides guidelines (e.g., development process and objectives to satisfy in development activities) for meeting safety requirements. This paper presents a modeling methodology including a UML profile for specifying safety requirements on a component-based architecture model and a set of design guidelines on avionics software. These safety requirements were identified from both standards (mainly DO-178B/C) and current engineering practices in the domain of avionics systems. The methodology automatically enforces these safety requirements. We have applied the methodology on an industrial autopilot system, and several previously uncaught faults were revealed. Copyright © 2014 John Wiley & Sons, Ltd.

关键词： Accident prevention

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